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, demographic modelling, Bayesian hierarchical models and/or modelling with multiple data streams • Experience with data science and biodiversity informatics, in particular handling of scientific collection
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qualifications: • Strong background in modelling, including spatial and temporal/dynamic modelling, demographic modelling, Bayesian hierarchical models and/or modelling with multiple data streams
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forecasting. Familiarity with ensemble methods, Bayesian approaches, and uncertainty estimation. Experience with large-scale or messy real-world data (structured and/or unstructured). Interest in or experience
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available: Chr. Michelsen Institute (CMI) currently has two vacancies for two postdoctoral researchers with an interest in cross-disciplinary work and expertise and knowledge of fresh groundwater networks
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project TAILOR – Network of Research Excellence Centres for Foundations of Trustworthy AI (2020-2024) , and EU project HiPEAC – Network of Excellence on High Performance, Edge And Cloud computing (2015-now
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strategies for safeguarding innovation, integrity, and cultural diversity against risks of exploitation and homogenization. The appointed candidate is expected to collaborate across the MishMash network and
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homogenization. The appointed candidate is expected to collaborate across the MishMash network and participate in all relevant MishMash activities. Research Proposal Applicants are required to upload a Research
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MSCA-PF proposals. For applicants awarded the MSCA-PF grant, we offer:• Inclusive, flexible, and friendly work environment• Access to a unique academic network• Norwegian language classes• Relocation
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competence in enzymology, fermentation and biorefining. KBM aims at a strong research position and collaborates in networks and research projects both nationally and internationally. For further information
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of the AI tools for the analysis of other creative artistic realms would be welcome, but not obligatory. The appointed candidate is expected to collaborate across the MishMash network and participate in all